The present invention relates to an HVAC system, and more particularly to bypassing a failed HVAC system component and/or stages to assure at least partial system capacity.
A heating, ventilating, and air conditioning (HVAC) system includes multiple components that function together in a coordinated manner. Typically, an HVAC system includes an indoor unit such as a gas furnace or fan coil, an outdoor unit such as an A/C or heat pump, and a thermostat. More sophisticated systems may include a multi-zone control capacity with zone control and zone dampers. HVAC systems also frequently include subsystems such as filters, humidifiers, and ventilators.
Typical HVAC systems include multiple stages of heating and/or cooling capacity. At the lowest demand, the first (lowest capacity) stage is activated. As demand increases past the capacity of the lowest stage, the next higher capacity stage is activated. If a lower capacity stage has failed, the component will “stage up” past the failed stage until enough capacity is brought on to satisfy the load. However, this may not be optimal as staging delays and temperature drop occur during the time in which the conventional component stages through the failed stage. Moreover, conventional controllers are unaware of failed stages within the remote HVAC components. If the highest capacity stage is the non-functional stage, the control will maintain operation of the system at this highest stage that has failed while providing no conditioning as conditioning demand continues to increase. The result may be complete loss of conditioning.
Accordingly, it is desirable to provide an HVAC system control that identifies and isolates a failed HVAC system and/or stages on a system wide level to assure at least partial system capacity while minimizing delays within a staging sequence by monitoring a temperature of a controlled area. It is further desirable for an HVAC system to learn component and stage capacities such that the specific system performance information is incorporated into the system control algorithm to optimize control over a wide range of system capacities.